Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

correct event_dim use #1661

Merged
merged 2 commits into from
Oct 11, 2023
Merged

correct event_dim use #1661

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
9d0756e
correct event_dim use
deoxyribose Oct 11, 2023
96d1239
test
deoxyribose Oct 11, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion numpyro/distributions/batch_util.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -577,7 +577,7 @@ def _promote_batch_shape_masked(d: MaskedDistribution):
def _promote_batch_shape_independent(d: Independent):
new_self = copy.copy(d)
new_base_dist = promote_batch_shape(d.base_dist)
new_self._batch_shape = new_base_dist.batch_shape[: d.event_dim]
new_self._batch_shape = new_base_dist.batch_shape[: -d.event_dim]
new_self.base_dist = new_base_dist
return new_self

Expand Down
6 changes: 3 additions & 3 deletions test/contrib/test_control_flow.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -213,7 +213,7 @@ def transition_fn(c, val):


def test_scan_plate_mask():
def model(y=None, T=10):
def model(y=None, T=12):
def transition(carry, y_curr):
x_prev, t = carry
with numpyro.plate("N", 10, dim=-1):
Expand All @@ -237,7 +237,7 @@ def transition(carry, y_curr):
return (x, y)

with numpyro.handlers.seed(rng_seed=0):
model_density, model_trace = log_density(model, (None, 10), {}, {})
model_density, model_trace = log_density(model, (None, 12), {}, {})
assert model_density
assert model_trace["x"]["fn"].batch_shape == (10,)
assert model_trace["x"]["fn"].batch_shape == (12, 10)
assert model_trace["x"]["fn"].event_shape == (3,)
Loading